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# coding=utf-8
# Implements stream chat in command line for fine-tuned models.
# Usage: python cli_demo.py --model_name_or_path path_to_model --checkpoint_dir path_to_checkpoint
from utils import (
Template,
load_pretrained,
prepare_infer_args,
get_logits_processor
)
from threading import Thread
from transformers import TextIteratorStreamer
def main():
model_args, data_args, finetuning_args, generating_args = prepare_infer_args()
model, tokenizer = load_pretrained(model_args, finetuning_args)
model_name = "BLOOM" if "bloom" in model_args.model_name_or_path else "LLaMA"
prompt_template = Template(data_args.prompt_template)
def predict_and_print(query, history: list) -> list:
input_ids = tokenizer([prompt_template.get_prompt(query, history)], return_tensors="pt")["input_ids"]
input_ids = input_ids.to(model.device)
streamer = TextIteratorStreamer(tokenizer, timeout=60.0, skip_prompt=True, skip_special_tokens=True)
gen_kwargs = generating_args.to_dict()
gen_kwargs["input_ids"] = input_ids
gen_kwargs["logits_processor"] = get_logits_processor()
gen_kwargs["streamer"] = streamer
thread = Thread(target=model.generate, kwargs=gen_kwargs)
thread.start()
print("{}: ".format(model_name), end="", flush=True)
response = ""
for new_text in streamer:
print(new_text, end="", flush=True)
response += new_text
print()
history = history + [(query, response)]
return history
history = []
print("欢迎使用 {} 模型，输入内容即可对话，clear清空对话历史，stop终止程序".format(model_name))
while True:
try:
query = input("\nInput: ")
except UnicodeDecodeError:
print("Detected decoding error at the inputs, please set the terminal encoding to utf-8.")
continue
except Exception:
raise
if query.strip() == "stop":
break
if query.strip() == "clear":
history = []
print("History has been removed.")
continue
history = predict_and_print(query, history)
if __name__ == "__main__":
main()
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